This invention is related in general to digital processing systems and more specifically to a system for modeling, analyzing and predicting the behavior of-a process or system by correlating the results of other analysis.
Computer systems provide powerful analysis tools in business, research, education, government and other fields. One field of interest includes the analysis of financial markets and instruments. For example, stock, bond, option, commodity and derivatives trading has been the subject of many types of published techniques, whether automated (“agents”) or manual. As the field of financial analysis has progressed, these techniques have become more numerous and varied. Often different techniques may work well in some situations, or for a certain period of time, but will fail to provide desirable results in other situations or at other periods of time.
For example, one technique may be to combine the performance of a group of stocks of companies in a common market, such as production of natural gas and oil. The general movement of the group of companies (i.e., up or down in price) can be used to predict the probable movement of another individual company in the same market. While this technique might work well where general market trends are the dominating factor in the market's price, the technique might not work well or even at all when a singular factor, such as an excessively high price to earnings ratio, can cause a company's current stock price to decline even when the general market trend for the that company's industry is increasing.
Some techniques may operate on simple concepts but may use variables -or parameters that must be characterized or selected by a human user or operator in order to arrive at an analysis or prediction. For example, the common measure of a “moving average” of a stock's price is a simple calculation but the start and end of the time period used to calculate the moving average can be infinitely variable. Other parameters can include the resolution of samples (e.g., per day, hour, minute, etc.), the manner of display of the results (e.g., table, plot, bar graph), and the type of data to which the technique is applied.
Although traditional techniques have proven to be useful for prediction and analysis of systems such as financial markets, as the number and complexity of techniques grows it is often difficult for a human user of the techniques to effectively use the techniques and to combine or correlate the various results provided by the techniques.